Print Email Facebook Twitter A Rapid Grid-Search Technique for KBO Exploration Trajectories Title A Rapid Grid-Search Technique for KBO Exploration Trajectories Author Benayas Penas, Miguel (TU Delft Aerospace Engineering) Contributor Cowan, K.J. (mentor) Hughes, K.M. (mentor) Visser, P.N.A.M. (graduation committee) Cervone, A. (graduation committee) Degree granting institution Delft University of Technology Programme Aerospace Engineering Date 2020-01-07 Abstract The Kuiper Belt is considered to be formed by remnants of the original Solar System, that is why exploration missions to that region are susceptible of having an enormous scientific impact. Nonetheless, it is far away from Earth, missions to KBO targets a significant challenge. Additionally, current methods to identify trajectories that encounter multiple KBOs are computationally intensive with impractically long run times on the order of months.The present work deals with applying a rapid low-fidelity technique to identify candidate preliminary KBO sequences, to be used as a starting point for futuremission designers to identify trajectories tomultiple KBOs. This pathfinding approach uses two consecutive grid search types. First, awell-tuned grid search is implemented using Lambert arcs to reach a first KBO, including the introduction of a new, systematic approach to identify the step sizes in target-body arrival date for the Lambert-based grid search. Then, second and third KBO encounters are assessed from the results of the first grid search and second KBO search respectively. Both second and third KBO searches are performed with a new algorithm consisting of a time grid along with STM linear propagation for maneuver calculation. Finally, an example trajectory resulting from this technique that encounters two KBOs is given as a potential flyable route. Subject PathfindingGrid SearchKuiper BeltOptimisationMission designTrajectory Design To reference this document use: http://resolver.tudelft.nl/uuid:7d9668d9-1aff-4ced-9fbd-04186a333c1d Part of collection Student theses Document type master thesis Rights © 2020 Miguel Benayas Penas Files PDF Miguel_Benayas_Penas_MSc_Thesis.pdf 3.46 MB Close viewer /islandora/object/uuid:7d9668d9-1aff-4ced-9fbd-04186a333c1d/datastream/OBJ/view